Project description:Outbreaks from zoonotic sources represent a threat to both human disease as well as the global economy. Despite a wealth of metagenomics studies, methods to leverage these datasets to identify future threats are underdeveloped. In this study, we describe an approach that combines existing metagenomics data with reverse genetics to engineer reagents to evaluate emergence and pathogenic potential of circulating zoonotic viruses. Focusing on the severe acute respiratory syndrome (SARS)-like viruses, the results indicate that the WIV1-coronavirus (CoV) cluster has the ability to directly infect and may undergo limited transmission in human populations. However, in vivo attenuation suggests additional adaptation is required for epidemic disease. Importantly, available SARS monoclonal antibodies offered success in limiting viral infection absent from available vaccine approaches. Together, the data highlight the utility of a platform to identify and prioritize prepandemic strains harbored in animal reservoirs and document the threat posed by WIV1-CoV for emergence in human populations.
Project description:Severe acute respiratory syndrome coronavirus 2 Delta variant epidemiology in Africa is unknown. We found Delta variant was introduced in Benin during April-May 2021 and became predominant within 2 months, after which a steep increase in reported coronavirus disease incidence occurred. Benin might require increased nonpharmaceutical interventions and vaccination coverage.
Project description:The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases 1-3 . The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions 4,5 . Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta's invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.
Project description:The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta’s invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.
Project description:Municipal wastewater provides an integrated sample of a diversity of human-associated microbes across a sewershed, including viruses. Wastewater-based epidemiology (WBE) is a promising strategy to detect pathogens and may serve as an early-warning system for disease outbreaks. Notably, WBE has garnered substantial interest during the COVID-19 pandemic to track disease burden through analyses of SARS-CoV-2 RNA. Throughout the COVID-19 outbreak, tracking SARS-CoV-2 in wastewater has been an important tool for understanding the spread of the virus. Unlike traditional sequencing of SARS-CoV-2 isolated from clinical samples, which adds testing burden to the healthcare system, in this study, metatranscriptomics was used to sequence virus directly from wastewater. Here, we present a study in which we explored RNA viral diversity through sequencing 94 wastewater influent samples across seven treatment plants (WTPs), collected August 2020 - January 2021, representing approximately 16 million people in Southern California. Enriched viral libraries identified a wide diversity of RNA viruses that differed between WTPs and over time, with detected viruses including coronaviruses, influenza A, and noroviruses. Furthermore, single nucleotide variants (SNVs) of SARS-CoV-2 were identified in wastewater and we measured proportions of overall virus and SNVs across several months. We detected several SNVs that are markers for clinically-important SARS-CoV-2 variants, along with SNVs of unknown function, prevalence, or epidemiological consequence. Our study shows the potential of WBE to detect viruses in wastewater and to track the diversity and spread of viral variants in urban and suburban locations, which may aid public health efforts to monitor disease outbreaks. Importance: Wastewater based epidemiology (WBE) can detect pathogens across sewersheds, which represents the collective waste of human populations. As there is a wide diversity of RNA viruses in wastewater, monitoring the presence of these viruses is useful for public health, industry, and ecological studies. Specific to public health, WBE has proven valuable during the COVID-19 pandemic to track the spread of SARS-CoV-2 without adding burden to healthcare systems. In this study, we used metatranscriptomics and RT-ddPCR to assay RNA viruses across Southern California wastewater from August 2020 - January 2021, representing approximately 16 million people from Los Angeles, Orange, and San Diego counties. We found that SARS-CoV-2 quantification in wastewater correlates well with county-wide COVID-19 case data, and that we can detect SARS-CoV-2 single nucleotide variants through sequencing. Likewise, WTPs harbored different viromes, and we detected other human pathogens such as noroviruses and adenoviruses, furthering our understanding of wastewater viral ecology.
Project description:Coronavirus disease 2019 (COVID-19) has emerged in December 2019 when the first case was reported in Wuhan, China and turned into a pandemic with 27 million (September 9th) cases. Currently, there are over 95,000 complete genome sequences of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, in public databases, accompanying a growing number of studies. Nevertheless, there is still much to learn about the viral population variation when the virus is evolving as it continues to spread. We have analyzed SARS-CoV-2 genomes to identify the most variant sites, as well as the stable, conserved ones in samples collected in the Netherlands until June 2020. We identified the most frequent mutations in different geographies. We also performed a phylogenetic study focused on the Netherlands to detect novel variants emerging in the late stages of the pandemic and forming local clusters. We investigated the S and N proteins on SARS-CoV-2 genomes in the Netherlands and found the most variant and stable sites to guide development of diagnostics assays and vaccines. We observed that while the SARS-CoV-2 genome has accumulated mutations, diverging from reference sequence, the variation landscape is dominated by four mutations globally, suggesting the current reference does not represent the virus samples circulating currently. In addition, we detected novel variants of SARS-CoV-2 almost unique to the Netherlands that form localized clusters and region-specific sub-populations indicating community spread. We explored SARS-CoV-2 variants in the Netherlands until June 2020 within a global context; our results provide insight into the viral population diversity for localized efforts in tracking the transmission of COVID-19, as well as sequenced-based approaches in diagnostics and therapeutics. We emphasize that little diversity is observed globally in recent samples despite the increased number of mutations relative to the established reference sequence. We suggest sequence-based analyses should opt for a consensus representation to adequately cover the genomic variation observed to speed up diagnostics and vaccine design.